Artificial intelligence (AI) has profoundly transformed our lives, with pervasive applications ranging from content creation, medical diagnostics, and so on. In the wave of AI, machine learning has laid the foundation for the rapid development of AI and aroused great interest. However, in real environments, the assumptions of machine learning are often not met. There are various imperfect scenarios that can cause the performance of machine learning models to drop significantly or unpredictable behaviors. Developing trustworthy machine learning systems in imperfect scenarios is important. In this chapter, we will briefly introduce the basic concepts of machine learning and trustworthy machine learning, laying the foundation for the content of subsequent chapters.